Iterative Pseudo-Soft-Reliability-Based Majority-Logic Decoding for NAND Flash Memory

Park, Kyeong Bin; Chung, Ki-Seok

doi:10.1109/access.2021.3079939

Cited by 3 publications

(2 citation statements)

References 29 publications

(43 reference statements)

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“…Inspired by the method of calculating its initial reliability in reference [18], the Hamming distance coefficient θ…”

Section: Simplified Design Of the Hamming Distance Coefficientmentioning

confidence: 99%

Research on Low-Density Parity-Check Decoding Algorithm for Reliable Transmission in Satellite Communications

He,

Wang

2024

Applied Sciences

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Satellite communications face difficulties such as intensified environmental attenuation, dynamic time-varying links, and diverse business scenarios, which usually require channel coding schemes with high coding gain and high throughput. Low-density parity-check (LDPC) codes are dominant in satellite communication coding schemes due to their excellent performance in approaching the Shannon limit and the characteristics of parallel computing. The traditional weighted-Algorithm B decoding algorithm ignores the channel received information and involves frequent multiplication operations and iteration, which introduces the channel received information for hard-decision and constellation mapping processing. Meanwhile, we design the correlated reliability between the extrinsic information and the mapping processing information to improve the correctness of decoding. The multiplication operation in the iterative process can be replaced by the simple sum of the Hamming distance coefficient, the correlated reliability between the extrinsic information and the mapping processing information, and the extrinsic information frequency, thereby reducing the complexity and storage load of the system. The simulation results show that the presented MRAI-LDPC algorithm can obtain about 0.4 dB performance gain, and the average number of iterations is reduced by 68% under a low SNR. The algorithm can achieve better error-correcting performance and higher throughput, providing strong support for reliable transmission of satellite communications.

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“…Inspired by the method of calculating its initial reliability in reference [18], the Hamming distance coefficient θ…”

Section: Simplified Design Of the Hamming Distance Coefficientmentioning

confidence: 99%

Research on Low-Density Parity-Check Decoding Algorithm for Reliable Transmission in Satellite Communications

He,

Wang

2024

Applied Sciences

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“…The distance between two binary strings is the total amount of different bits at the same position [45]. We select Hamming Distance for our system based on its good performance application for recognition as well as for decoding application where similarity is used as the primary measurement for the system or method performance [46], [47], [48], [49].…”

Section: Hamming Distancementioning

confidence: 99%

Intelligent Military Aircraft Recognition and Identification to Support Military Personnel on the Air Observation Operation

Sumari¹,

Adinandra²,

Syulistyo³

et al. 2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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A hostile or unfriendly aircraft will mostly fly at low-level altitude or hide behind natural obstacles to avoid Radar detection. One of the ways to detect and recognize while at the same time identifying such aircraft is to perform air observation from the ground. A technique called Visual Aircraft Recognition (VACR) has been practiced in training soldiers to recognize and find an incoming aircraft from a distance using binoculars. Remembering so many types of aircraft have their challenge. To ease the task, we have designed and developed an intelligent military aircraft recognition and identification system using the combination of Back Propagation Neural Networks (BPNN) and Information Fusion to speed up the recognition and identification. We use 13 aircraft features fused into five primary ones as the inputs to the BPNN for the recognition, while the identification uses Hamming Distance to the recognition results. With 155 data consisting of 85 military aircraft and helicopters and 70 civilian aircraft and helicopters and applying the 80:20 scheme for the training and test data, our system can obtain 95.33% and 87% accuracy at the training phase and the test phase. It also succeeds in recognizing and identifying a new military aircraft that is not in the dataset, while the Information Fusion can speed up the recognition and identification by up to 6 seconds. This impacts the acceleration of aircraft recognition and identification.

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Trapping and Absorbing Set Enumerators for Nonbinary Protograph-Based Low-Density Parity-Check Code Ensembles

Yacoub

Liva

2023

IEEE Trans. Commun.

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Iterative Pseudo-Soft-Reliability-Based Majority-Logic Decoding for NAND Flash Memory

Cited by 3 publications

References 29 publications

Research on Low-Density Parity-Check Decoding Algorithm for Reliable Transmission in Satellite Communications

Research on Low-Density Parity-Check Decoding Algorithm for Reliable Transmission in Satellite Communications

Intelligent Military Aircraft Recognition and Identification to Support Military Personnel on the Air Observation Operation

Trapping and Absorbing Set Enumerators for Nonbinary Protograph-Based Low-Density Parity-Check Code Ensembles

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